Premium
Exploring the optimal sampling density to characterize spatial heterogeneity of soil carbon stocks in a Karst Region
Author(s) -
Zhang zhenming,
Zhou Yunchao,
Huang Xianfei
Publication year - 2020
Publication title -
agronomy journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.752
H-Index - 131
eISSN - 1435-0645
pISSN - 0002-1962
DOI - 10.1002/agj2.20467
Subject(s) - karst , spatial variability , environmental science , sampling (signal processing) , soil science , soil carbon , spatial distribution , stock (firearms) , spatial heterogeneity , sampling design , soil water , hydrology (agriculture) , geology , mathematics , statistics , geography , ecology , paleontology , filter (signal processing) , geotechnical engineering , biology , computer science , computer vision , population , demography , archaeology , sociology
The aim of this study is to investigate the spatial distribution of soil organic C stock and to determine the optimal number of samples required for its determination, in a small karst basin. By taking the soil organic C stock in the Houzhai River Basin, calculated on the basis of a 150 by 150 m grid sampling design as original data and selecting sample sets at five grid scales (300, 450, 600, 750, and 900 m), the optimal number of samples for different sampling distances was obtained, using geographic information system (GIS) technology and geostatistical analyses. With increasing sampling distance, the coefficient of variation of the soil organic C stocks first increased and then decreased; the spatial predictions of the soil organic C stock tended to be smoother, and the ability to represent detail was weaker. The prediction accuracy was comprehensively discussed. When the surface soil organic C stock (0–20 cm) was considered, 357 sampling points at a sampling distance of 450 by 450 m could accurately represent its spatial variability. For a depth of 0–100 cm, 200 sampling points and a sampling distance of 600 m could accurately represent the spatial variability in the soil organic C stock. The results of this study could provide data for future studies for the estimation of soil organic C stock in the karst areas of Southwest China and similar areas.